GFZ-GEM Phase 2 Publication List
2019
Mak S, Cotton F, Schorlemmer D, Hirata N (2019) Testing the Official Seismic Hazard Model for Japan. Nature Geoscience: submitted
2018
Chen, Y, Weatherill, G, Pagani, M, Cotton, F (2018): A transparent and data-driven global tectonic regionalisation model for seismic hazard assessment. - Geophysical Journal International, 213, 2, pp. 1263-1280.
Mak S, Cotton F, Gerstenberger M, Schorlemmer D (2018): An Evaluation of the Applicability of NGA‐West2 Ground‐Motion Models for Japan and New Zealand. Bulletin of the Seismological Society of America 108(2): 836-856. DOI: http://doi.org/10.1785/0120170146
Schorlemmer D, Werner MJ, Marzocchi W, Jordan TH, Ogata Y, Jackson DD, Mak S, Rhoades DA, Gerstenberger MC, Hirata N, Liukis M, Maechling PJ, Strader A, Taroni M, Wiemer S, Zechar JD, Zhuang J (2018): The Collaboratory for the Study of Earthquake Predictability: Achievements and Priorities. Seismological Research Letters 89(3): in print
Strader A, Werner M, Bayona J, Maechling P, Silva F, Liukis M, Schorlemmer D (2018): Prospective evaluation of global earthquake forecast models: Two years of observations support merging smoothed seismicity with geodetic strain rates. Seismological Research Letters 89(3): in print
Taroni M, Marzocchi W, Schorlemmer D, Werner MJ, Wiemer S, Zechar JD, Heiniger L, Euchner F (2018): Prospective CSEP evaluation of 1-day, 3-month, and 5-year earthquake forecasts for Italy. Seismological Research Letters 89(3): in print
2017
Mak S, Clements R, Schorlemmer D (2017): Empirical Evaluation of Hierarchical Ground‐Motion Models: Score Uncertainty and Model Weighting. Bulletin of the Seismological Society of America 107(2): 949-965. DOI: http://doi.org/10.1785/0120160232
Mak S, Clements RA, Schorlemmer D (2017): Empirical Evaluation of Hierarchical Ground-Motion Models: Score Uncertainty and Model Weighting. Bulletin of the Seismological Society of America 107(2): 949-965. DOI: http://doi.org/10.1785/0120160232
Mak S, Cotton F, Schorlemmer D (2017): Measuring the Performance of Ground‐Motion Models: The Importance of Being Independent. Seismological Research Letters 88: 1212-1217. DOI: http://doi.org/10.1785/0220170097
Pittore M, Wieland M, Fleming K (2017): Perspectives on global dynamic exposure modelling for geo-risk assessment. Natural Hazards 86(Suppl. 1): 7-30.
Strader A, Schneider M, Schorlemmer D (2017): Prospective and retrospective evaluation of five-year earthquake forecast models for California. Geophysical Journal International 211(1): 239-251. DOI: http://doi.org/10.1093/gji/ggx268
2016
Mai PM, Schorlemmer D, Page M, Ampuero JP, Asano K, Causse M, Custodio S, Fan WY, Festa G, Galis M, Gallovic F, Imperatori W, Kaeser M, Malytskyy D, Okuwaki R, Pollitz F, Passone L, Razafindrakoto HNT, Sekiguchi H, Song SG, Somala SN, Thingbaijam KKS, Twardzik C, van Driel M, Vyas JC, Wang RJ, Yagi Y, Zielke O (2016): The Earthquake-Source Inversion Validation (SIV) Project. Seismological Research Letters 87(3): 690-708. DOI: http://doi.org/10.1785/0220150231
Mak S, Clements R, Schorlemmer D (2016): Reply to “Comment on ‘Validating Intensity Prediction Equations for Italy by Observations’ by Sum Mak, Robert Alan Clements, and Danijel Schorlemmer” by Mathias Raschke. Bulletin of the Seismological Society of America 106(5): 2414-2415. DOI: http://doi.org/10.1785/0120160200
Mak S, Schorlemmer D (2016): A Comparison between the Forecast by the United States National Seismic Hazard Maps with Recent Ground‐Motion Records. Bulletin of the Seismological Society of America 106(4): 1817-1831. DOI: http://doi.org/10.1785/0120150323
Mak S, Schorlemmer D (2016): Erratum to Validating Intensity Prediction Equations for Italy by Observations. Bulletin of the Seismological Society of America 106(2): 813-813. DOI: http://doi.org/10.1785/0120150358
Mak S, Schorlemmer D (2016): What Makes People Respond to “Did You Feel It?”?. Seismological Research Letters 87(1): 119-131. DOI: http://doi.org/10.1785/0220150056
Wieland M, Pittore M (2016): Large-area settlement pattern recognition from Landsat-8 data. ISPRS Journal of Photogrammetry and Remote Sensing 119: 294–308.
2015
Bindi D, Boxberger T, Orunbaev S, Pilz M, Stankiewicz J, Pittore M, Iervolino I, Ellguth E, Parolai S (2015): On-site early-warning system for Bishkek (Kyrgyzstan). Annals of Geophysics 58(1): S0112.
Gordon JS, Clements RA, Schoenberg FP, Schorlemmer D (2015): Voronoi residuals and other residual analyses applied to CSEP earthquake forecasts. Spatial Statistics 14: 133-150, Part: B. DOI: http://doi.org/10.1016/j.spasta.2015.06.001
Mak S, Clements R, Schorlemmer D (2015): Validating Intensity Prediction Equations for Italy by Observations. Bulletin of the Seismological Society of America 105(6): 2942-2954. DOI: http://doi.org/10.1785/0120150070
Mak S, Clements RA, Schorlemmer D (2015): Validating Intensity Prediction Equations for Italy by Observations. Bulletin of the Seismological Society of America 105(6): 2942-2954. DOI: http://doi.org/10.1785/0120150070
Mikhailova NN, Mkambayev AS, Aristova IL, Kulikova G, Ullah S, Pilz M, Bindi D (2015): Central Asia earthquake catalogue from ancient time to 2009. Annals of Geophysics 58(1): S0102.
Pittore M (2015): Focus maps: a means of prioritizing data collection for efficient geo-risk assessment. Annals of Geophysics 58(1): S0107.
Saponaro A, Pilz M, Bindi D, Parolai S (2015): The contribution of EMCA to landslide susceptibility mapping in Central Asia. Annals of Geophysics 58(1): S0113.
Stankiewicz J, Bindi D, Oth A, Parolai S (2015): Toward a cross-border early-warning system for Central Asia. Annals of Geophysics 58(1): S0111.
Ullah S, Bindi D, Pilz M, Parolai S. (2015): Probabilistic seismic hazard assessment for Central Asia. Annals of Geophysics 58(1): S0103.
Wieland M, Pittore M, Parolai S, Begaliev U, Yasunov P, Tyagunov S, Moldobekov B, Saidiy S, Ilyasov I, Abakanov T (2015): A Multiscale Exposure Model for Seismic Risk Assessment in Central Asia. Seismological Research Letters 86(1): 210–222.
2014
Holschneider M, Zoeller G, Clements R, Schorlemmer D (2014): Can we test for the maximum possible earthquake magnitude? Journal of Geophysical Research-Solid Earth 119(3): 2019-2028. DOI: http://doi.org/10.1002/2013JB010319
Mak S, Clements R, Schorlemmer D (2014): Comment on "A New Procedure for Selecting and Ranking Ground-Motion Prediction Equations (GMPEs): The Euclidean Distance-Based Ranking (EDR) Method" by Ozkan Kale and Sinan Akkar. Bulletin of the Seismological Society of America 104(6): 3139-3140. DOI: http://doi.org/10.1785/0120140106
Mak S, Clements R, Schorlemmer D (2014): The Statistical Power of Testing Probabilistic Seismic-Hazard Assessments. Seismological Research Letters 85(4): 781-783. DOI: http://doi.org/10.1785/0220140012
Mak S, Clements RA, Schorlemmer D (2014): Comment on "A New Procedure for Selecting and Ranking Ground-Motion Prediction Equations (GMPEs): The Euclidean Distance-Based Ranking (EDR) Method" by Ozkan Kale and Sinan Akkar. Bulletin of the Seismological Society of America 104(6): 3139-3140. DOI: http://doi.org/10.1785/0120140106
Mak S, Clements RA, Schorlemmer D (2014): The Statistical Power of Testing Probabilistic Seismic-Hazard Assessments. Seismological Research Letters 85(4): 781-783. DOI: http://doi.org/10.1785/0220140012
Pittore M, Bindi D, Stankiewicz J, Oth A, Wieland M, Boxberger T, Parolai S (2014): Toward a Loss-Driven Earthquake Early Warning and Rapid Response System for Kyrgyzstan (Central Asia). Seismological Research Letters 85(6): 1328–1340.
Rhoades DA, Gerstenberger MC, Christophersen A, Zechar JD, Schorlemmer D, Werner MJ, Jordan TH (2014): Regional Earthquake Likelihood Models II: Information Gains of Multiplicative Hybrids. Bulletin of the Seismological Society of America 104(6): 3072-3083. DOI: http://doi.org/10.1785/0120140035
Schneider M, Clements R, Rhoades D, Schorlemmer D (2014): Likelihood- and residual-based evaluation of medium-term earthquake forecast models for California. Geophysical Journal International 198(3): 1307-1318. DOI: http://doi.org/10.1093/gji/ggu178
Wieland M, Pittore M (2014): Performance Evaluation of Machine Learning Algorithms for Urban Pattern Recognition from Multi-spectral Satellite Images. Remote Sensing 6(4): 2912–2939.